Wenjie Wei

Wenjie Wei

UESTC

Hello👋! This is Wenjie Wei（卫文杰）. I am currently a Ph.D. student (from fall 2022) in the School of Computer Science and Engineering at the University of Electronic Science and Technology of China (Chengdu, Sichuan). I am supervised by Prof. Malu Zhang（张马路）. Prior to joining UESTC, I obtained my Bachelor’s degree from Zhengzhou University in 2021.

My research interests broadly encompass Brain-inspired Computing, Spiking Neural Networks, Model Compression, Neuromorphic Vision, etc. I have published more than 20 papers at the top international AI conferences/journals with a total Google Scholar citations .

💬 Academic Services

  • Journal Reviewer: Neural Networks, IEEE TETCI, IEEE TCDS, IEEE TBioCAS, Neurocomputing, Frontiers in Neuroscience, etc.
  • Conference Reviewer: NeurIPS, ICLR, ICML, CVPR, AAAI, IJCAI, etc.
  • Invited Oral Presentation titled “Event-Driven Learning for Spiking Neural Networks”, at the 11th IEEE International Conference on CIS-RAM Young Scholars Workshop.
  • Core Contributor of the WeChat Official Account named “Progress in Brain-Inspired Intelligence”, regularly shares the latest developments in the Brain-Inspired Intelligence field.

🔥 News

  • 2025.09:  🎉🎉 One survey paper about EEG and SNNs is accepted by Neural Networks.
  • 2025.09:  🎉🎉 Three papers are accepted by NeurIPS-2025.
  • 2025.09:  🎉🎉 One survey paper about Photonic Chips and SNNs is accepted by Nanophotonics.
  • 2025.08:  🎉🎉 One paper is accepted by IEEE Trans. Evolutionary Computation.
  • 2025.07:  🎉🎉 One paper is accepted by ACMMM-2025.
  • 2025.06:  🎉🎉 One paper is accepted by Neural Networks.
  • 2025.05:  🎉🎉 One paper is accepted by ICML-2025.
  • 2025.04:  🎉🎉 One paper is accepted by IJCAI-2025.
  • 2025.02:  🎉🎉 One paper is accepted by CVPR-2025 (Oral, 3.3%).
  • 2025.01:  🎉🎉 Two papers are accepted by ICLR-2025.
  • 2024.12:  🎉🎉 One paper is accepted by AAAI-2025 (Oral, 4.5%).
  • 2024.12:  🎉🎉 Created my own personal homepage.

📝 Publications

Survey Papers

Neural Networks
sym

Spiking Neural Networks for EEG Signal Analysis: From Theory to Practice

Siqi Cai, Zheyuan Lin, Xiaoli Liu, Wenjie Wei✉, Shuai Wang, Malu Zhang, Tanja Schultz, Haizhou Li

  • The review encompasses foundational knowledge of SNNs, detailed implementation strategies for EEG analysis, and challenges inherent to SNN-based methods.
  • |
Nanophotonics
sym

What Is Next for LLMs? Next-Generation AI Computing Hardware Using Photonic Chips

Renjie Li†, Qi Xin†, Wenjie Wei, Xiaoli Liu, Sixuan Mao, Erik Ma, Zijian Chen, Malu Zhang, Haizhou Li, Zhaoyu Zhang

  • This review surveys emerging photonic hardware optimized for next-generation generative AI computing.

Selected Papers

NeurIPS 2025
sym

S2NN: Sub-bit Spiking Neural Networks

Wenjie Wei, Malu Zhang✉, Jieyuan Zhang, Ammar Belatreche, Shuai Wang, Yimeng Shan, Hanwen Liu, Honglin Cao, Guoqing Wang, Yang Yang, Haizhou Li

  • This work introduces sub-bit SNNs, which compress synaptic weights to below one bit using outlier-aware sub-bit quantization and membrane potential-based feature distillation, achieving state-of-the-art efficiency and performance for edge computing applications.

ICLR 2025
sym

QP-SNNs: Quantized and Pruned Spiking Neural Networks

Wenjie Wei, Malu Zhang✉, Zijian Zhou, Ammar Belatreche, Yimeng Shan, Yu Liang, Honglin Cao, Jieyuan Zhang, Yang Yang

  • This paper proposes QP-SNN, a lightweight and hardware-friendly model that combines weight rescaling-based quantization with singular value-based pruning for efficient edge deployment.

ACM MM 2024
sym

Q-SNNs: Quantized Spiking Neural Networks

Wenjie Wei, Yu Liang, Ammar Belatreche, Yichen Xiao, Honglin Cao, Zhenbang Ren, Guoqing Wang, Malu Zhang✉, Yang Yang

  • This paper introduces quantized spiking neural networks with binary weights and low-bit membrane potentials, along with a Weight-Spike Dual Regulation method, to achieve energy efficiency and high performance.

  • |

ICCV 2023
sym

Temporal-coded spiking neural networks with dynamic firing threshold: Learning with event-driven backpropagation

Wenjie Wei, Malu Zhang✉, Hong Qu, Ammar Belatreche, Jian Zhang, Hong Chen

  • This paper introduces a dynamic firing threshold and direct training algorithm that enable temporal-coded SNNs to achieve high accuracy and energy efficiency.

  • |

Others

  • Temporal-coded Spiking Transformer.
    Qian Sun, Chengzhuo Lu, Wenyu Chen, Wenjie Wei✉, Jingya Wang, Jieyuan Zhang, Xiaoli Liu, Yalan Ye, Yang Yang, Malu Zhang

  • ESTSformer: Efficient Spatio-Temporal Spiking Transformer.
    Chengzhuo Lu, Huilin Du, Wenjie Wei✉, Qian Sun, Yuchen Wang, Dingyi Zeng, Wenyu Chen, Malu Zhang, Yang Yang

  • Spike-Driven Lightweight Large Language Model With Evolutionary Computation.
    Malu Zhang, Wenjie Wei (Student First Author), Zijian Zhou, Wanlong Liu, Jie Zhang, Ammar Belatreche, Yang Yang

  • Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism.
    Yu Liang, Wenjie Wei, Ammar Belatreche, Honglin Cao, Zijian Zhou, Shuai Wang, Malu Zhang, Yang Yang

  • BSO: Binary Spiking Online Optimization Algorithm.
    Yu Liang, Yu Yang, Wenjie Wei, Ammar Belatreche, Shuai Wang, Malu Zhang, Yang Yang

  • Binary Event-Driven Spiking Transformer.
    Honglin Cao†, Zijian Zhou†, Wenjie Wei, Ammar Belatreche, Yu Liang, Dehao Zhang, Malu Zhang, Yang Yang, Haizhou Li

  • Quantized Spike-driven Transformer.
    Xuerui Qiu†, Malu Zhang, Jieyuan Zhang†, Wenjie Wei, Honglin Cao, Junsheng Guo, Rui-Jie Zhu, Yimeng Shan, Yang Yang, Haizhou Li

  • Rethinking Spiking Self-Attention Mechanism: Implementing a-XNOR Similarity Calculation in Spiking Transformers.
    Yichen Xiao†, Shuai Wang†, Dehao Zhang, Wenjie Wei, Yimeng Shan, Xiaoli Liu, Yulin Jiang, Malu Zhang

  • Spike-based Neuromorphic Model for Sound Source Localization.
    Dehao Zhang†, Shuai Wang†, Ammar Belatreche, Wenjie Wei, Yichen Xiao, Haorui Zheng, Zijian Zhou, Malu Zhang, Yang Yang

  • Towards Energy-Efficient Spike-Based Deep Reinforcement Learning With Temporal Coding.
    Malu Zhang, Shuai Wang, Jibin Wu, Wenjie Wei, Dehao Zhang, Zijian Zhou, Siying Wang, Fan Zhang, Yang Yang

  • Memory-Free and Parallel Computation for Quantized Spiking Neural Networks.
    Dehao Zhang, Shuai Wang, Yichen Xiao, Wenjie Wei, Yimeng Shan, Malu Zhang, Yang Yang

  • Ternary spike-based neuromorphic signal processing system.
    Shuai Wang, Dehao Zhang, Ammar Belatreche, Yichen Xiao, Hongyu Qing, Wenjie Wei, Malu Zhang, Yang Yang

  • Event-driven learning for spiking neural networks.
    Wenjie Wei, Malu Zhang, Jilin Zhang, Ammar Belatreche, Jibin Wu, Zijing Xu, Xuerui Qiu, Hong Chen, Yang Yang, Haizhou Li

  • Sdtrack: A baseline for event-based tracking via spiking neural networks. |
    Yimeng Shan, Zhenbang Ren, Haodi Wu, Wenjie Wei, Rui-Jie Zhu, Shuai Wang, et al.

🏆 Honors and Awards

  • 2025.08: Best Dataset & Benchmark Award, IJCAI2025-SpikeCV Competition: Infinity-WUJI. (Only 1 Team Worldwide)
  • 2022.11: Outstanding Student Leader, University of Electronic Science and Technology of China.
  • 2021.09: First-Class Scholarship, University of Electronic Science and Technology of China.
  • 2021.06: Outstanding Graduate, Zhengzhou University.
  • 2019, 2020.11: National Encouragement Scholarship, Zhengzhou University.
  • 2018.11: Outstanding Contributor in Social Service, Zhengzhou University.

📖 Educations

  • 2022.09 - 2026.06, Ph.D. Candidate in School of Computer Science and Engineering, University of Electronic Science and Technology of China. (Supervisor: Malu Zhang)
  • 2021.09 - 2022.06, M.S. in School of Computer Science and Engineering, University of Electronic Science and Technology of China.
  • 2017.09 - 2021.06, B.S. in School of Information Engineering, Zhengzhou University.